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As doctors and researchers explore the effectiveness of treating cancer patients with combinations of chemotherapy drugs, their attention has largely been focused on how much of each drug to give.
A new study has found that achieving best results may also require looking into how much time should pass between delivering one drug and the next.
Researchers led by members of the Department of Systems Biology at Harvard Medical School had been studying how silencing MDMX, an oncogene, affected the dynamics of p53, a natural tumor suppressor, in cancer cells when they realized those dynamics might affect the cells’ sensitivity to a second, chemotherapy-like treatment.
Live imaging of single cells revealed that time wildly affected cell survival. A short wait between disabling MDMX and administering chemotherapy made the two treatments synergistic, killing cancer cells more effectively than either would have alone, while a longer wait led to treatment resistance, allowing more cancer cells to withstand attack.
“This is the first time someone has shown that timing makes such a big difference in cells’ response to combination therapy,” said Galit Lahav, professor of systems biology at HMS and senior author of the paper, published March 10 in Science. “It’s a first look at how one treatment can change the internal state of individual cells to make them more or less sensitive to a second treatment.”
The findings indicate that testing combination treatments at only one time point, whether in lab experiments or clinical trials, may not tell the whole story.
“Right now, cancer clinical trials that use multiple drugs give them simultaneously,” said Sheng-hong Chen, a postdoctoral researcher in the Lahav lab and first author of the paper. “Our work shows that you need to understand the biology at the single-cell level to determine whether timing matters and to design an optimal schedule.”
The study also provides a new way to screen for small molecules that inhibit MDMX.
A few years ago, Chen was trying to study a biochemical process involving p53 when he noticed something odd: When he eliminated MDMX to simplify the system, p53 levels started swinging up and down.
The Lahav lab had previously reported p53 oscillations in single cells following DNA damage, but this time Chen hadn’t prodded p53 with any such external signals. So he decided to do a quantitative analysis of MDMX’s effects on p53 by studying individual cells across time—a specialty of the Lahav lab.
He used an siRNA (small interfering RNA) to render the MDMX gene inert in a line of breast cancer cells (MCF-7) and a line of immortalized noncancerous retinal pigment epithelium (RPE) cells.
At first, nothing happened. But when a cell divided for the first time after being treated, p53 surged in a single pulse before slowly falling again. In the ensuing hours, p53 wobbled through a series of smaller oscillations. Chen and Lahav labeled the surge and the subsequent oscillations “phase one” and “phase two.”
Since he had coupled p53 to a fluorescent tag, Chen could watch its glow swell and then diminish from hour to hour under a microscope.
“These were interesting dynamics that no one had found before,” Chen said.
Previous studies had disagreed on whether eliminating MDMX raised or lowered p53 levels. Chen and Lahav believe the dynamics were masked because those studies looked at whole populations of cells that were dividing and entering “phase one” at different times.
Many chemotherapy drugs work by damaging DNA, which cancer cells are less able to withstand than normal cells. Because p53 helps kill cells in reaction to DNA damage, the researchers hypothesized that its surge would raise cancer cells’ susceptibility to chemotherapy.
After suppressing MDMX, the researchers waited varying amounts of time before delivering a second treatment that damaged the cells’ DNA.
Sure enough, the cells were more sensitive to the second treatment when it was delivered during phase one, when p53 was at its peak: 95 percent of cells died, compared to about 66 percent when the DNA-damaging treatment was given alone. But to the team’s surprise, the cells became less sensitive during phase two: only 16 percent died.
“This suggests there may be a sharp window during which you want to hit cells with a second drug,” said Chen.
Questions remain before the researchers’ findings can be translated to the clinic.
For instance, cells in a tumor may not divide at the same time, making it hard to determine how long to wait between administering a first and second drug.
“We have a limited understanding of how cells are synchronized in the body,” said Chen. “It’s possible that circadian rhythms help align cell cycles, but we don’t know.”
The team’s experiments suggest that at least for the cell dynamics explored in the current study, 12 hours may allow enough time for a majority of the cells to enter phase one, while 48 hours may be too late.
“Most studies, including drug-screening campaigns, infer cellular behavior from the averages of much larger populations,” said study co-author William Forrester, a longtime collaborator of the Lahav lab and senior research investigator at the Novartis Institutes for Biomedical Research, which partially funded the study. “The insight that treatment timing is the difference between sensitivity and resistance represents an opportunity to revisit combination therapy.”
This study was supported by the National Institutes of Health (grants GM083303 and F32GM105205) and the Novartis Institutes for Biomedical Research.
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